Estimating minute ventilation and air pollution inhaled dose using heart rate, breath frequency, age, sex and forced vital capacity: A pooled-data analysis
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Estimating minute ventilation and air pollution inhaled dose using heart rate, breath frequency, age, sex and forced vital capacity: A pooled-data analysis

机译:使用心率,呼吸频率,年龄,性别和强迫肺活量估算分钟通气量和空气污染吸入剂量:汇总数据分析

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摘要

Air pollution inhaled dose is the product of pollutant concentration and minute ventilation (V˙E). Previous studies have parameterized the relationship between V˙E and variables such as heart rate (HR) and have observed substantial inter-subject variability. In this paper, we evaluate a method to estimate V˙E with easy-to-measure variables in an analysis of pooled-data from eight independent studies. We compiled a large diverse data set that is balanced with respect to age, sex and fitness level. We used linear mixed models to estimate V˙E with HR, breath frequency (fB), age, sex, height, and forced vital capacity (FVC) as predictors. FVC was estimated using the Global Lung Function Initiative method. We log-transformed the dependent and independent variables to produce a model in the form of a power function and assessed model performance using a ten-fold cross-validation procedure. The best performing model using HR as the only field-measured parameter was V˙E = e-9.59HR2.39age0.274sex-0.204FVC0.520 with HR in beats per minute, age in years, sex is 1 for males and 2 for females, FVC in liters, and a median(IQR) cross-validated percent error of 0.664(45.4)%. The best performing model overall was V˙E = e-8.57HR1.72fB0.611age0.298sex-0.206FVC0.614, where fB is breaths per minute, and a median(IQR) percent error of 1.20(37.9)%. The performance of these models is substantially better than any previously-published model when evaluated using this large pooled-data set. We did not observe an independent effect of height on V˙E, nor an effect of race, though this may have been due to insufficient numbers of non-white participants. We did observe an effect of FVC such that these models over- or under-predict V˙E in persons whose measured FVC was substantially lower or higher than estimated FVC, respectively. Although additional measurements are necessary to confirm this finding regarding FVC, we recommend using measured FVC when possible.
机译:空气污染吸入剂量是污染物浓度和分钟通风量的乘积( < > V ˙ E )。先前的研究已经参数化了 V ˙ E 和诸如心率(HR)的变量,并观察到受试者之间存在很大的差异。在本文中,我们评估一种方法来估算 V ˙ E 带有易于测量的变量,可用于分析来自八项独立研究的汇总数据。我们编制了一个庞大的多样化数据集,该数据集在年龄,性别和健康水平方面保持平衡。我们使用线性混合模型来估算 V ˙ E 以HR,呼吸频率(fB),年龄,性别,身高和强迫肺活量(FVC)作为预测因子。 FVC是使用“全球肺功能计划”方法估算的。我们对因变量和自变量进行对数转换,以生成幂函数形式的模型,并使用十倍交叉验证程序评估了模型性能。使用HR作为唯一实地测量参数的最佳性能模型是 V ˙ E = e -9.59 HR 2.39 age 0.274 sex -0.204 FVC 0.520 ,每分钟心率HR,以岁为单位,男性性别为1,女性为2,FVC以升为单位,交叉验证的中位数(IQR)误差百分比为0.664(45.4) )%。总体上表现最佳的模型是 V ˙ E = e -8.57 HR 1.72 fB 0.611 age 0.298 sex -0.206 FVC 0.614 ,其中fB是每分钟呼吸次数,中位数(IQR)百分比误差为1.20(37.9)%。当使用此大型汇总数据集进行评估时,这些模型的性能明显优于任何以前发布的模型。我们没有观察到身高对 的独立影响 V ˙ E ,也不是种族的影响,尽管这可能是由于非白人参与者人数不足所致。我们确实观察到了FVC的影响,使得这些模型高估或低估了 V ˙ E < / mi> 分别测量的FVC显着低于或高于估计的FVC。尽管需要额外的测量来确认有关FVC的发现,但我们建议尽可能使用测量的FVC。

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